Online citizen science projects engage volunteers in collecting, analyzing, and curating scientific data. Existing projects have demonstrated the value of using volunteers to collect data, but few projects have reached the full collaborative potential of scientists and volunteers. Understanding the shared and unique motivations of these two groups can help designers establish the technical and social infrastructures needed to promote effective partnerships. We present findings from a study of the motivational factors affecting participation in ecological citizen science projects. We show that volunteers are motivated by a complex framework of factors that dynamically change throughout their cycle of work on scientific projects; this motivational framework is strongly affected by personal interests as well as external factors such as attribution and acknowledgment. Identifying the pivotal points of motivational shift and addressing them in the design of citizen-science systems will facilitate improved collaboration between scientists and volunteers.
6. Research Questions What are the major motivational factors affecting volunteers and scientists’ engagement in citizen science projects? 1 What are the major motivational barriers to such collaboration? 2
7. Methods Survey 18 interviews Scientists (44%) Volunteers (56%) Most participants had more than 1 year of experience Participants Scientists n = 62 (44%) Volunteers n = 80 (56%) Experience Less than a year Scientists Volunteers n = 16 n = 35 (25%) (44%) More than a year Scientists Volunteers n = 46 n = 45 (75%) (56%) Gender Male Scientists Volunteers n = 38 n = 46 (60%) (57%) Female Scientists Volunteers n = 24 n = 34 (40%) (43%) N = 142 Magnusfrankkun @ Flickr
8. Principles of social participation Egoism Principalism Collectivism Altruism Batson, Ahmed and Chang, 2002 yarotman Buckeye98 @Flickr Liam Q @ Flickr [email_address]
10. Process model of scientists’ and volunteers’ collaboration Without scientists’ recognition = loss of motivation Personal interest initial or ongoing Initial involvement Interaction with scientists Recognition Training, attribution, feedback Continued involvement Ongoing attribution, inclusion in scientific work, community involvement , advocacy egoism egoism Egoism, collectivism, altruism Without scientists’ continued recognition = loss of motivation Scientists’ need for data Scientists’ altruistic support for public education
11. Motivations for collaboration - scientists Education and outreach “ I don’t think people can make good decisions, be it policy or environmental or anything else, unless they understand how things work. This provides the opportunity to educate people through a valid citizen science program” Data needs “ I see [volunteers] as most helpful in making accurate observations… they are basically the field component”
12. Motivations for collaboration - volunteers Primary motivation - personal interest “ I think personal interest comes first. Personal interest and personal gain”. “ I would be less inclined to participate in something I had little interest in, even if it was a worthy endeavor”
13. Motivations for collaboration - volunteers Secondary motivations - recognition and attribution “ I’m not really, obviously, objected to glory. I do expect attribution… I would always like to be the first one to put a photo up there, it’s got to count somehow” “ It’s not about spending time or money. It’s more about the constant feedback to the volunteers that what we’re doing is useful and being used” “ people going through the thorough training feel like they’re contributing a lot more”
14. Motivations for collaboration - volunteers Feedback “ It’s the combination of being an affective citizen scientist and seeing the community thrive… people really care about their natural resources here” “ It’s a perfect opportunity to help people understand their environment. I hope that something that you say will make a dent and make them more curious and they’ll go home and pick a book or they’ll call you back” Secondary motivations - community involvement and advocacy
15. De-motivating factors “ Scientists are intimidating” “ Scientists speak a different jargon” “ they are just so unfriendly!” Volunteers Scientists “ they may potentially contaminate the data” “ we need quality control!” “ people won’t come back if there isn’t a loop of credibility and trust and things that they can see that are being accomplished as a result of the data they are collecting”
16. Process model of scientists’ and volunteers’ collaboration Without scientists’ recognition = loss of motivation Personal interest initial or ongoing Initial involvement Interaction with scientists Recognition Training, attribution, feedback Continued involvement Ongoing attribution, inclusion in scientific work, community involvement , advocacy egoism egoism Egoism, collectivism, altruism Without scientists’ continued recognition = loss of motivation Scientists’ need for data Scientists’ altruistic support for public education
18. Designing for continuous collaboration Highlighting data use and reuse http://www.divematrix.com/showthread.php?9520-hehehehe-Hermit-Crab-movin-on-up!
20. Designing for continuous collaboration Break tasks into smaller building blocks; support synergy Ksgr @ Flickr
21. Designing for continuous collaboration Match scientists, volunteers and tasks muhawi001@ Flickr Jessi.bryan @ Flickr
22. Future work Facilitate better ways to get volunteers to come back and continuously engage in citizen science collaborations Examine the process model across cultures and disciplines 1 2
Following initial interest there were some secondary motivators, very important ones nonetheless, that volunteers presented. Although volunteers clearly accepted the roles of scientists as leaders of the scientific process, they looked for recognition, manifested through attribution. They wanted to be appreciated for their contribution, no matter how small. Singling out contributions. Important especially when artifacts or data were used in scientific publications. ] Alternative – participation in what was seen as scientific work. Training, teaching, initiation into the scientific world. They actually valued repetitive traning, having to invest time and money. They liked it when projects upheld them to rigorous standards and they seemed to like that more than projects that were less rigid about what they did and when.
Once volunteers were already involved in citizen science projects, the impact of their work on their local community became an influential motivating factor. volunteers stressed their continued commitment to scientific projects that were taking place in their area because of their potential effect on their community. Example - citizens collected samples from streams and rivers which were previously deemed not fit for commercial harvesting. When the contamination level lowered and these areas reopened for commercial fishing, they boosted the local economy. Following that, participation in related citizen science projects rose steadily.
Mutual apprehension Not acknowledging each other’s motivations trust
the design should enable identification of points in which participation declines (or can decline) such as the end of a task, and interject the proper motivational probes. For example, when a project is initiated, recruitment materials can emphasize the inherent interest of the topic and volunteers‟ chance to learn, but materials provided to recruited volunteers should emphasize opportunities for recognition, advanced training, and social engagement.
he system needs to make available information about where, how and to what extent the data were used, in order to provide feedback to the volunteers. Automatic reminders or system prompts